pre-commit 으로 코드 정리 및 포맷팅 개선

Author: ehddnr301

interface/lang2sql.py

@@ -117,11 +117,13 @@ def should_show(_key: str) -> bool:
                 st.write(f"적합성 통과 여부: `{passed}`")
             try:
                 import json as _json
-                st.code(_json.dumps(details, ensure_ascii=False, indent=2), language="json")
+
+                st.code(
+                    _json.dumps(details, ensure_ascii=False, indent=2), language="json"
+                )
             except Exception:
                 st.write(details)
 
-
     if should_show("show_token_usage"):
         st.markdown("---")
         token_summary = TokenUtils.get_token_usage_summary(data=res["messages"])

llm_utils/chains.py

@@ -7,6 +7,7 @@
 - Profile Extraction
 - Question Gate (SQL 적합성 분류)
 """
+
 import os
 from langchain_core.prompts import (
     ChatPromptTemplate,
@@ -29,6 +30,7 @@ class QuestionProfile(BaseModel):
 
     이 프로파일은 이후 컨텍스트 보강 및 SQL 생성 시 힌트로 사용됩니다.
     """
+
     is_timeseries: bool = Field(description="시계열 분석 필요 여부")
     is_aggregation: bool = Field(description="집계 함수 필요 여부")
     has_filter: bool = Field(description="조건 필터 필요 여부")
@@ -126,4 +128,4 @@ def create_question_gate_chain(llm):
 query_maker_chain = create_query_maker_chain(llm)
 profile_extraction_chain = create_profile_extraction_chain(llm)
 query_enrichment_chain = create_query_enrichment_chain(llm)
-question_gate_chain = create_question_gate_chain(llm)
+question_gate_chain = create_question_gate_chain(llm)

llm_utils/graph_utils/base.py

@@ -36,6 +36,7 @@ class QueryMakerState(TypedDict):
     device: str
     question_gate_result: dict
 
+
 # 노드 함수: QUESTION_GATE 노드
 def question_gate_node(state: QueryMakerState):
     """

llm_utils/graph_utils/basic_graph.py

@@ -25,9 +25,11 @@
 builder.add_node(GET_TABLE_INFO, get_table_info_node)
 builder.add_node(QUERY_MAKER, query_maker_node)
 
+
 def _route_after_gate(state: QueryMakerState):
     return GET_TABLE_INFO
 
+
 builder.add_conditional_edges(
     QUESTION_GATE,
     _route_after_gate,

llm_utils/graph_utils/enriched_graph.py

@@ -31,9 +31,11 @@
 builder.add_node(CONTEXT_ENRICHMENT, context_enrichment_node)
 builder.add_node(QUERY_MAKER, query_maker_node)
 
+
 def _route_after_gate(state: QueryMakerState):
     return GET_TABLE_INFO
 
+
 builder.add_conditional_edges(
     QUESTION_GATE,
     _route_after_gate,

llm_utils/output_parser/__init__.py

@@ -3,4 +3,3 @@
 
 이 패키지는 LLM의 구조화 출력 모델과 파서들을 포함합니다.
 """
-

llm_utils/output_parser/question_suitability.py

@@ -21,5 +21,3 @@ class QuestionSuitability(BaseModel):
     requires_data_science: bool = Field(
         default=False, description="SQL을 넘어 ML/통계 분석이 필요한지 여부"
     )
-
-